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Two major leaps in AI-powered drug discovery
AI + Medicine Newsletter 2024–03–12
1. From AI to Clinical Trials: Fast-tracking Anti-fibrotic Drug Development
The AI-predicted TNIK inhibitor, INS018_055, showcases a rapid transition from AI-based target discovery to clinical validation, offering a new treatment avenue for fibrosis. This study from Insilico Medicine, one of the pioneers in AI for drug discovery, highlights the efficiency of AI in drug discovery, evidenced by the swift 18-month progression from identifying the target to nominating a preclinical candidate, promising a faster route to developing therapies for fibrotic diseases.
For target identification, they used PandaOmics, a cloud-based platform that applies AI and bioinformatics techniques to multimodal omics and biomedical text data for target and biomarker discovery. They even posted a video to show the PandaOmics workflow can identify the TNIK gene as the top targeting candidate in a couple of minutes. (Although we are not sure how long it took them to decide the settings in the workflow and whether the same settings can be directly applied to another disease quickly and successfully.)
For small molecule design, they used Chemistry42, which includes 42 generative models and more than 500…
